"Psychedelic drugs can distort our reality and result in perceptual illusions. But the reality we experience during ordinary wakefulness is also, to a large extent, an illusion."

How our sense of vision works provides just one example of this.

"We know that the brain fills in visual information when suddenly missing, that veins in front of the retina are filtered out and not perceived, and that the brain stabilizes our visual perception in spite of constant eye movements," Tagliazucchi explained. "So when we take psychedelics we are, it could be said, replacing one illusion by another illusion. This might be difficult to grasp, but our study shows that the sense of self or ‘ego' could also be part of this illusion."

Tagliazucchi, Robin Carhart-Harris of Imperial College London, and their colleagues scanned the brains of 15 healthy people while they were on LSD versus a placebo.

The scientists discovered that LSD inflated the level of communication between normally distinct brain networks. The higher the test subjects became, the more they reported a sense of ego dissolution.

The researchers linked this feeling to increased global connectivity within the individuals' frontoparietal cortex, which is a brain region associated with self-consciousness. They noted, in particular, increased connection between this portion of the brain and sensory areas that are in charge of receiving information about the world around us and conveying it for further processing to other brain areas.

"This could mean that LSD results in a stronger sharing of information between regions, enforcing a stronger link between our sense of self and the sense of the environment and potentially diluting the boundaries of our individuality," Tagliazucchi said.

He and his team also observed changes in the functioning of a part of the brain previously linked to "out-of-body" experiences, in which people feel as though they have left their bodies. Other drugs, such as ketamine and PCP, can create such sensations in users too, with some people even having near-death sensations.

These drugs can be highly addictive, with clear associated dangers. The jury is still out, however, on whether frequent usage of drugs like LSD can directly cause brain damage - resulting in mental disorders such as schizophrenia - or whether the drugs just intensify symptoms within those already afflicted with one or more mental illnesses.

Tagliazucchi believes that psychedelic drugs have value to science when administered in controlled research settings.

He next plans to use neuroimaging to explore various states of consciousness, including sleep, anesthesia, and coma. He additionally hopes to make direct comparisons between people in a dream versus a psychedelic state.

Imperial College London researchers are also investigating other psychedelic drugs and their potential use in the treatment of disorders. These include depression and anxiety.

It's easy to mistake this photo for some kind of surreal landscape painting, but this image in fact shows off the imagination of Google's advanced image detection software.
Similar to an artist with a blank canvas, Google's software constructed this image out of nothing, or essentially nothing, anyway. This photo began as random noise before software engineers coaxed this pattern out of their machines.
How is it possible for software to demonstrate what appears to be an artistic sensibility? It all begins with what is basically an artificial brain.

Artificial neural networks are systems consisting of between 10 and 30 stacked layers of synthetic neurons. In order to train the network, "each image is fed into the input layer, which then talks to the next layer, until eventually the 'output' layer is reached,"

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The layers work together to identify an image. The first layer detects the most basic information, such as the outline of the image. The next layers hone in on details about the shapes. The final output layer provides the "answer," or identification of the subject of an image.
Shown is Google's image software before and after processing an image of two ibis grazing to detect their outlines.

Searching for shapes in clouds isn't just a human pastime anymore.
Google engineers trained the software to identify patterns by feeding millions of images to the artificial neural network. Give the software constraints, and it will scout out patterns to recognize objects even in photos where the search targets are not present.
In this photo, for example, Google's software, like a daydreamer staring at the clouds, finds all kinds of different animals in the sky. This pattern emerged because the neural network was trained primarily on images of animals.

How the machine is trained will determine its bias in terms of recognizing certain objects within an otherwise unfamiliar image.
In this photo, a horizon becomes a pagoda; a tree is morphed into building; and a leaf is identified as a bird after image processing.
The objects may have similar outlines to their counterparts, but all of the entries in the "before" images aren't a part of the software's image vocabulary, so the system improvises.

When the software acknowledges an object, it modifies a photo to exaggerate the presence of that known pattern. Even if the software is able to correctly recognize the animals it has been trained to spot, image detection may be a little overzealous in identifying familiar shapes, particularly after the engineers send the photo back, telling the software to find more of the same, and thereby creating a feedback loop.
In this photo of a knight, the software appears to recognize the horse, but also renders the faces of other animals on the knight's helmet, globe and saddle, among other places.

Taken a step further, using the same image over several cycles in which the output is fed through over and over again, the artificial neural network will restructure an image into the shapes and patterns it has been trained to recognize.
Again borrowing from an image library heavy on animals, this landscape scene is transformed into a psychedelic dream scene where clouds are apparently made of dogs.

At its most extreme, the neural network can transform an image that started as random noise into a recognizable but still somewhat abstract kaleidoscopic expression of objects with which the software is most familiar.
Here, the software has detected a seemingly limitless number of arches in what was a random collection of pixels with no coherence whatsoever.

This landscape was created with a series of buildings.
Google is developing this technology in order to boost its image recognition software. Future photo services might recognize an object, a location or a face in a photo.
The engineers also suggest that the software could one day be a tool for artists that unlocks a new form of creative expression and may even shed light on the creative process more broadly.